- maim
- xclip
Set this on your i3 config file ~/.i3/config
# Screenshots
| (async () => { | |
| 'use strict'; | |
| // ============================================================ | |
| // codex-quota-compass.js(发布版) | |
| // ============================================================ | |
| // 用法:在 https://chatgpt.com/codex/cloud/settings/analytics#usage | |
| // 或任意 chatgpt.com 页面打开 DevTools Console,粘贴运行。 | |
| // | |
| // 安全: |
| // ==UserScript== | |
| // @name GLM Coding Rush - 智谱编程助手抢购脚本 | |
| // @namespace https://gist.github.com/LessUp | |
| // @version 1.1.0 | |
| // @description 智谱 GLM Coding 一键抢购脚本 — 自动解锁售罄按钮 / 高速重试引擎 / bizId 双重校验 / 错误弹窗自动恢复 / 支付弹窗保护 / 秒级定时触发 / 可拖拽浮动面板 | |
| // @author LessUp | |
| // @match *://www.bigmodel.cn/* | |
| // @match https://bigmodel.cn/glm-coding* | |
| // @run-at document-start | |
| // @grant none |
Hyper-V in Windows 10 and Windows 11 allows running Virtual Machine. It is supported only in Pro, Enterprise and Education Edition of Windows 10 and Windows 11 by default. But this guide will show you how to enable it in Home Editions of Windows 10 and Windows 11.
Command Prompt in Windows Start Menu and open it.systeminfo and press Enter. Wait for the process to finishHyper-V Requirements section which is usually the last one.
A hypervisor has been detected. Features required for Hyper-V will not be displayed. that means Hyper-V is already enabled and there is no reason following this guide anymore.Virtualization Enabled in Firmware:.A pattern for building personal knowledge bases using LLMs.
This is an idea file, it is designed to be copy pasted to your own LLM Agent (e.g. OpenAI Codex, Claude Code, OpenCode / Pi, or etc.). Its goal is to communicate the high level idea, but your agent will build out the specifics in collaboration with you.
Most people's experience with LLMs and documents looks like RAG: you upload a collection of files, the LLM retrieves relevant chunks at query time, and generates an answer. This works, but the LLM is rediscovering knowledge from scratch on every question. There's no accumulation. Ask a subtle question that requires synthesizing five documents, and the LLM has to find and piece together the relevant fragments every time. Nothing is built up. NotebookLM, ChatGPT file uploads, and most RAG systems work this way.
| # LLM Wiki — [YOUR FIELD] | |
| A personal knowledge base of [YOUR FIELD] papers, following [Karpathy's LLM Wiki pattern](https://gist.github.com/karpathy/1dd0294ef9567971c1e4348a90d69285): | |
| ``` | |
| Original PDF → sources/*.md (LLM summary) → wiki/{category}/*.md (final page) | |
| ``` | |
| **Language policy**: All wiki content is in English. Conversation can be in any language. |